Increasingly, search and retrieval techniques for non-text based data are becoming desirable. Text-based searching has improved by leaps and bounds over the Internet and the World-Wide Web (WWW) in recent years. Virtually everyone is familiar with the ever-popular Internet search engine Google®. Yet, very little improvement or advancement has been made with respect to image search and retrieval.
One of the most common approaches to searching images is to affix text labels and text metadata with images and then permit a text search to retrieve image data by matching to the metadata and then linking to the images. In fact, this is an approach that Google® users. However, the text-based approach requires retrofitting image data with proper metadata and also does not permit a raw image to be used as a search; rather, an image has to first be described in text terms before a search can proceed.
In addition to user-initiated searches, many searches are performance based and done unbeknownst to the users. That is, to improve response times for users that seek information and resources over a network, such as the Internet, behind the scenes services conduct search for that information within a cache to see if it is already present and can be quickly delivered to the user. When a cache search is unsuccessful, this produces a cache miss and results in the desired information being acquired from its source. Because searching the cache takes some time, if misses are more frequent then the user's response times can quickly degrade such that the cache implementation becomes more of a liability rather than a benefit to the user.
Cache misses are particularly prevalent when images are cached because the techniques for searching images are not that robust and suffer from many drawbacks as discussed above. Thus, when a cache is heavily populated with images the cache misses steadily increase and administrators question whether a cache-based solution is even viable.
Thus, what are needed are techniques, which allow for improved caching of images.